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Abstract Background: Quality of life (QOL) assessment is an important component within cancer research. There is often variability in QOL scores both between patients and across time. Understanding this variability in terms of personal characteristics and psychosocial factors would be useful but is often obstructed by the types of analyses that are applied to longitudinal data sets. Improved understanding can be gained with the application of multi-level or hierarchical models that allow for greater flexibility for modelling individual patterns of change over time. Methods and patients: Questionnaires were sent to a cohort of stage IV melanoma patients seen at the Sydney Melanoma Unit between 1991 and 1996, approximately every 3 months for up to 2 years. The data reported here are from a sub-sample of 44 patients who each completed between 3 and 8 questionnaires. Three aspects of QOL were measured (effort to cope, mood and physical well-being), each with a single LASA line. Multilevel techniques were used to model the patterns of QOL over time. Covariates were added to explain variation between patients in their average QOL and change in QOL over time. Results: The scores of each of the three QOL measures showed marked fluctuations over time. However, there was little systematic change during the study in either effort to cope ( p = 0.32) or mood ( p = 0.06). In contrast, the physical well-being scores of some patients improved while others deteriorated ( p 〈 0.001). On average, physical well-being deteriorated ( p 〈 0.001). Variability between patients accounted for 60% (effort to cope), 45% (mood) and 44% (physical well-being) of the total variance of each scale. A range of psycho-social factors including active and avoidant coping styles and psychological adjustment accounted for significant amounts of the variability between patients in each QOL measure. Conclusion: Individual coping and psychological adjustment are related to individual changes in QOL and to differences among patients' QOL. The study illustrates the use of multi-level techniques to further our understanding of differences between patients in their QOL and how it changes over time.